Advanced Parkinson disease (APD) is often under-recognized, which may delay treatment optimization and referral for device-aided therapy assessment. Machine learning-enabled remote monitoring systems (ML-RMS) may support earlier recognition of progression, but their value depends on whether alerts lead to clinical action and patient benefit.

We developed a Markov model comparing standard care with ML-RMS-supported care from the Finnish health care perspective. The model simulated persons with Parkinson disease at risk of APD over 16 years. The base case assumed ML-RMS sensitivity and specificity of 88 percent and 62 percent. Costs, quality-adjusted life years (QALYs), incremental cost-effectiveness ratios, and incremental net monetary benefit were estimated. Scenario and probabilistic sensitivity analyses explored diagnostic accuracy, monitoring costs, direct quality-of-life effects, deep brain stimulation (DBS) costs, pathway timing, and delayed nursing home admission.

In the base case, ML-RMS generated 0.0044 additional QALYs at an additional cost of €761 per patient, resulting in an incremental cost-effectiveness ratio of €172,023 per QALY gained. At a willingness-to-pay threshold of €35,000 per QALY, the incremental net monetary benefit was negative. Scenario analyses indicated that ML-RMS could become cost-effective if active monitoring produced direct quality-of-life gains or delayed nursing home admission.

ML-RMS is unlikely to be economically favorable if limited to earlier APD recognition and timely DBS treatment in a small eligible subgroup. Its value depends on whether monitoring changes care pathways, improves patient outcomes, or reduces long-term care needs. Future studies should prioritize clinical utility, quality-of-life effects, treatment decisions, and institutional care.

To provide methodological enhancement to hospital-based Health Technology Assessment (HTA) by (i) analyzing technical-scientific reports produced by hospital-based HTA (HB-HTA) units and (ii) examining their relation to the identification of unmet medical needs (UMNs).

This study adopts a qualitative case study design, methodologically enhanced through the analysis of 37 HTA reports – technical-scientific reports (TSRs) – produced by the HTA Unit of the Hospital de Clínicas de Porto Alegre (HCPA), recognized as the leading public hospital in Latin America (according to IntelLat, 2025). Content analysis, guided by international references such as the NEED project, supported the improvement of the evaluation process of TSRs and their related UMNs.

Thirty-nine UMNs were identified across the 37 assessed technologies, predominantly therapeutic (56.8 percent) and diagnostic (32.4 percent), especially in neurology, oncology, and cardiology. Most technologies (89.2 percent) showed additional (Research and Development) R&D needs. The study also demonstrated improvements in the evaluation process of TSRs and the identification of related UMNs.

This study presents a methodological improvement that enables HTA reports to serve as structured sources of institutional intelligence. By identifying UMNs, the approach strengthens the role of HB-HTA in informing future R&D agendas. Replication in other hospital and health system contexts is recommended to consolidate its applicability and broaden its impact.

Hospitals may not preserve the assumptions approved for medical-equipment purchases alongside post-adoption financial and value outcomes. We specified a clinical service line (CSL) investment recovery framework and examined its initial feasibility using routine hospital records.

Targeted mapping of health technology assessment (HTA), lifecycle HTA, management accounting, and organizational learning concepts was followed by internal logic checks. A retrospective records-based application was conducted for one purposively selected 4 K arthroscopy camera-head investment at a Japanese acute-care hospital. Aggregate fixed-asset, lease, and claims records were analyzed descriptively without patient-level data or causal attribution.

The framework links CSL definition, pre-adoption commitments, annualized investment burden (AIB), contribution margin (CM), evidence status, allocation, value guardrails, and feedback. The 72-month lease had a total value of JPY 4,728,240 and a minimum documented annual burden of JPY 788,040. Shoulder arthroscopy volume increased from 220 to 245 procedures (11.4 percent), and nominal procedure-fee revenue increased from JPY 102.8 million to JPY 114.9 million (11.8 percent) between 12-month periods. Planned values, variable costs, direct use logs, and prespecified quality or access indicators were unavailable; CM-based recovery metrics could not be calculated. The documented annual burden equaled JPY 31,522 per observed additional procedure, or 6.52 percent of the observed revenue increase under full attribution.

The framework operationalizes hospital-level post-adoption and lifecycle HTA as an auditable CSL process. The application demonstrated partial data availability and identified fields that must be preserved prospectively; it did not establish causality, actual recovery, acceptability, or decision impact.

Health Technology Assessment (HTA) agencies often lay out the methods and processes for recommendations through guidelines. However, evidence suggests that the presence of guidelines does not necessarily lead to more systematic, evidence-based decisions. This article explores the differentiating features of HTA guidelines that have successfully promoted change in decision-making practice.

We compared the development and impact of HTA guidelines over time in eight countries through a multi-case study design. Data from interviews and literature review were analyzed qualitatively by pattern matching.

In settings without a guideline owner, guidelines were most successful if the development process targeted key stakeholders who are able to influence change in an open process of joint learning, and an agency with relevant expertise was assigned to oversee future guideline implementation and revisions. In settings with a clear guideline owner, guidelines were most successful if stakeholders continued to be engaged after guideline publication, to incorporate interim updates and when there was continuous learning between stakeholders and the HTA agency. Enforcing guideline compliance through laws was not found to be a predictor of guideline success nor was the level of HTA institutionalization in a country.

At any stage of HTA institutionalization, HTA guideline success depends on whether the development and revision process successfully builds shared understanding and trust among stakeholders. Ensuring HTA guideline impact requires an open and inclusive approach to stakeholder engagement during and after guideline development, as well as effective accountability mechanisms for guideline ownership.

Orphan drug reimbursement remains a contested area in health technology assessment (HTA), as decision makers must balance limited evidence, high unmet need, patient-relevant value, and affordability. Multi-criteria decision analysis (MCDA) has been proposed to make such trade-offs more explicit and transparent, yet empirical applications in European national HTA settings remain scarce.

We developed and piloted an MCDA framework for orphan drug reimbursement in Belgium. Candidate criteria were identified through a systematic literature review. A multidisciplinary expert panel (comprising representatives from the national reimbursement agency, sickness funds, patient organizations, pharmaceutical companies, clinicians, and bioethicists) participated in four focus group discussions to select and define criteria. Criterion weights were elicited through a three-round Delphi process. The framework was piloted on four orphan drugs previously appraised in Belgium: ponatinib, pirfenidone, onasemnogene abeparvovec, and metreleptin.

Seven quantitative and three qualitative contextual criteria were selected. Unmet medical need received the highest weight, followed by comparative effectiveness and impact on patient-reported outcomes. Onasemnogene abeparvovec achieved the highest overall MCDA score (0.77), followed by metreleptin (0.65), pirfenidone (0.47), and ponatinib (0.39). The pilot also generated policy-relevant insights on criterion design, handling residual uncertainty, separating value assessment from reimbursement feasibility (through cost criteria), and using scores to support–rather than replace–deliberation.

This study presents the first MCDA framework for orphan drug reimbursement in Belgium and illustrates how criterion weights and scores can structure committee deliberation, complemented by contextual appraisal, to support more transparent, consistent, and accountable decision making.

The European Union (EU) has long pursued harmonization in medicines regulation and, more recently, in health technology assessment (HTA). The European Medicines Agency (EMA) and the EU HTA Regulation (EU HTAR) represent key milestones in these respective trajectories. This study compares the harmonization trajectories of EU medicines regulation and EU HTA to identify lessons relevant for EU HTAR implementation.

We used a multi-method qualitative approach combining a narrative literature review with online focus groups involving eighteen regulatory and policy experts. The review explored the historical development of harmonization in both policy areas. The focus-group analysis examined perspectives on collaboration, harmonization dynamics, and implementation.

Both policy areas moved from national arrangements and voluntary cooperation toward more formal EU-level structures. Medicines regulation developed earlier and resulted in more centralized procedures and binding EU-wide authorization decisions. EU HTA retains greater national responsibility for value judgments, pricing, and reimbursement. The two areas also differ in the scope and standardization of assessments. In both trajectories, harmonization was shaped by trust, willingness to collaborate, capacity differences, and legal and procedural contexts. Participants emphasized the importance of stepwise implementation, work sharing, and sustained dialogue, while anticipating variation in national JCA uptake and impact.

Experience from EU medicines regulation highlights the importance of building trust and adapting collaboration to differences in national maturity and priorities. Harmonization should develop gradually through learning and refinement across diverse legal and procedural contexts. These lessons may support EU HTAR implementation and further development.

Health innovation encounters challenges across the innovation lifecycle. Although various policy instruments aim to support innovation, their alignment with stage-specific challenges remains unclear. This study synthesizes evidence to examine how innovation challenges and policy responses are distributed across the health innovation lifecycle, with particular attention to the role of early Health Technology Assessment (early HTA).

We conducted an umbrella review of review-level studies that examined health innovation challenges and related policy instruments. A comprehensive literature search was performed across five databases, including PubMed, Web of Science, Embase, Scopus, and CINAHL. Twenty-four eligible studies were included and synthesized using a well-established analytical framework. Innovation challenges and policy instruments were mapped across stages of the development pathway and linked to the contributions of early HTA.

Innovation challenges were most pronounced in product design and clinical trial stages. Institutional barriers, including lengthy approval processes, became more prominent during regulatory approval and market access. Eighty policy responses were identified and clustered into economic, regulatory, and informational instruments. Economic measures were concentrated in product design and clinical trial stages, while regulatory instruments focused on regulatory approval and market access. Early HTA emerged as a complementary decision-support approach that may help address product design and clinical trial stages challenges.

There is a clear misalignment between where innovation challenges arise and where policy responses are applied. Integrating early HTA more systematically into innovation policy frameworks could help address challenges in product design and clinical trial stages and improve the likelihood of successful innovation adoption.

We examined long-term treatment-effect patterns relevant to treatment effect waning (TEW) modeling in oncology health technology assessment (HTA), compared the dispersion and update stability of hazard ratios (HRs) and restricted mean survival time ratios (RMSTRs), and developed prediction models to support extrapolation model selection and TEW modeling.

Using the FDA Hematology/Oncology Approvals Database, we identified phase II/III randomized controlled trials (2006-2025) with updates. We included overall survival (OS) and other time-to-event end points (non-OS). We conducted 2/3/4/5-year landmark analyses to estimate post-landmark HRs and RMSTRs, summarized by event-weighted medians and dispersion (coefficient of quartile relative dispersion, CQR). Update-related change was quantified using updated-to-initial ratios. We predicted longer-term RMSTR using elastic-net regression with nested cross-validation and split-conformal 90 percent prediction intervals.

We analyzed 168 trials (270 contrasts; 150 OS, 120 non-OS). Across landmark analyses at 2, 3, 4, and 5 years, RMSTR was consistently less dispersed than HR for both OS and non-OS end points, while post-landmark HRs generally remained < 1. Update ratios were more stable for RMSTR than HR. Initial and updated RMSTR were strongly correlated (OS r = .87; non-OS r = .82). Parsimonious regularized models accurately predicted updated RMSTR, with conformal prediction intervals achieving 91 percent and 96 percent coverage for OS and non-OS.

Reliance on current HR-based TEW modeling practices alone may be insufficient to fully characterize long-term treatment-effect uncertainty. RMSTR was consistently less dispersed than HR and predictable from early trial data, providing an anchor for extrapolation model selection and TEW uncertainty analysis in oncology economic evaluations.

Health technology assessment is emerging in Lebanon, with an increased interest in health economic evaluations (EEs). Despite the importance of the methodological quality of EEs, no study has examined this issue in Lebanon.

As only methodologically robust health EE can meaningfully inform decision making, this study systematically reviews and critically appraises published full EEs in Lebanon, formulating recommendations to strengthen the quality and consistency of future evaluations within the Lebanese context.

We searched for full model- and trial-based EEs and cost-minimization analyses (CMAs) on NHSEED, Medline, EMBASE, and CINAHL without language or time restrictions. We followed PRISMA guidelines, narratively synthesized the characteristics, methods, and results of studies, and critically appraised them using CHEC for trial-based evaluations and CMA and CHEC-Extended for model-based evaluations.

Eight studies, published 2012–2025, were included: five model-based, two trial-based, and one CMA. Assessed technologies included screening/vaccination programs, diagnostic tools, nutrition education, e-mental health interventions, and early versus delayed treatment of hepatitis C. Methodological inconsistencies pertained mostly to discounting rates and willingness-to-pay thresholds. Suboptimal quality pertained mainly to model-based evaluations conducted by Lebanese researchers. Common pitfalls included the perspective being unclear; the identification, measurement, and valuation of costs and outcomes; model validation and calibration; sensitivity analyses; and discounting. The trial-based and CMA met more than 80 percent of the criteria.

We identified a limited number of published full EEs in Lebanon and highlighted their major shortcomings. Future work should scale up high-quality EEs in Lebanon, particularly modeling studies, to inform resource allocation.